Phylogenetic ecology and the greening of cities
Bibliographic record
Abstract
Summary Ecologists are increasingly involved in city‐making, especially in the development of green infrastructure and other designed plant communities. Plant communities that are more phylogenetically related are more similar in functional traits and adaptations to their environment than distant relatives. Knowledge of how evolutionary relationships among plant species influence ecosystem functions could be applied to green infrastructure to improve benefits such as urban cooling, habitat creation and stormwater management. The intended outcomes of manipulations of phylogenetic diversity ( PD ) may vary depending on project goals, particularly when considering the trade‐offs between multiple ecosystem functions. For instance, constraining PD could improve survival and performance in stressful environments or short growing seasons. Increasing PD could improve habitat diversity, aesthetics and other direct human benefits. Synthesis and applications . Given the potential benefits of considering phylogenetic relationships of plant communities in green infrastructure, we recommend that ecologists work with landscape architects and other design professionals to test how ecophylogenetics – the application of phylogenies in ecology – might aid in achieving desired outcomes for green infrastructure.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".